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You searched for subject:(temporal coverage). Showing records 1 – 3 of 3 total matches.

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NSYSU

1. Hsu, Shin-En. An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks.

Degree: Master, Computer Science and Engineering, 2014, NSYSU

Rotatable and directional (R&D) sensors are wireless sensors that have the sector-like coverage range and rotation capability. These sensors can provide temporal coverage of objects by periodically rotating to monitor them. An object is called δi-time covered if it can be monitored by R&D sensor(s) for at least δi portion of a period, where 0 < δi ⤠1. Given a set of heterogeneous objects that have different δi-time covered requirements, the paper formulates a generalized R&D sensor deployment (GRSD) problem, which determines how to deploy the minimum number of R&D sensors to satisfy the coverage requirement of each object. We prove that the GRSD problem is NP-hard and develop an efficient heuristic to deploy R&D sensors based on the distribution and δi values of objects. Extensive simulation results show that our GRSD heuristic can save more sensors compared with other methods, which significantly reduces the deployment cost of R&D sensor networks. Advisors/Committee Members: You-Chiun Wang (committee member), Wei-Kuang Lai (chair), Chun-Hung Lin (chair), Bing-Hong Liu (chair).

Subjects/Keywords: point coverage; directional sensor; sensor deployment; wireless sensor network; temporal coverage

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hsu, S. (2014). An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0608114-135737

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hsu, Shin-En. “An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks.” 2014. Thesis, NSYSU. Accessed April 16, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0608114-135737.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hsu, Shin-En. “An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks.” 2014. Web. 16 Apr 2021.

Vancouver:

Hsu S. An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Apr 16]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0608114-135737.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hsu S. An Efficient Deployment Heuristic to Support Temporal Coverage of Heterogeneous Objects in Rotatable and Directional (R&D) Sensor Networks. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0608114-135737

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. SILVA, João Nailson de Castro. Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru.

Degree: 2017, Universidade Federal de Campina Grande; PÓS-GRADUAÇÃO EM RECURSOS NATURAIS; UFCG; Brasil; Centro de Tecnologia e Recursos Naturais – CTRN

Submitted by Lucienne Costa ([email protected]) on 2018-09-12T19:09:12Z No. of bitstreams: 1 JOÃO NAILSON DE CASTRO SILVA – DISSERTAÇÃO (PPGRN) 2017.pdf: 6066847 bytes, checksum: 06d6d215ba35522ddc64fb5c435d43f4 (MD5)

Made available in DSpace on 2018-09-12T19:09:12Z (GMT). No. of bitstreams: 1 JOÃO NAILSON DE CASTRO SILVA – DISSERTAÇÃO (PPGRN) 2017.pdf: 6066847 bytes, checksum: 06d6d215ba35522ddc64fb5c435d43f4 (MD5) Previous issue date: 2017-08-25

Capes

A Caatinga é um bioma único que só ocorre na região do Semiárido do Brasil (SAB). Este bioma se diferencia principalmente pela capacidade de desenvolver mecanismos de adaptação aos baixos índices pluviométricos da região, além de apresentar alta resiliência nesse ambiente de elevada pressão antrópica. Tendo em vista que a cobertura vegetal exerce um papel muito importante no equilíbrio ambiental, as técnicas de sensoriamento remoto têm sido muito utilizadas para extrair informações biofísicas da vegetação. Este trabalho, teve como objetivo estabelecer uma metodologia que incorpore a capacidade de caracterização temporal do índice de vegetação à técnica de classificação de imagens para melhorar a identificação das classes de cobertura da Terra na bacia do Rio Sucuru, no Cariri paraibano. Neste sentido, busca-se uma classificação de referência dos padrões de cobertura da terra a partir de imagens de SR, para um período específico, no qual, seja possível uma validação em campo. Além disso, é realizada uma avaliação de uma série temporal de um índice de vegetação para melhoria da classificação realizada. Nessa pesquisa foi adotado parte da metodologia proposta por Chaves et al. (2008), para classificar os padrões de cobertura do solo e uma série temporal de EVI, processadas com 88 imagens selecionadas dos sensores ETM+ e OLI/TIRS, da série Landsat, para o período entre outubro de 2014 a setembro de 2016. Os resultados evidenciaram que analisar a cobertura vegetal utilizando apenas um único momento não retrata fidedignamente os padrões de cobertura do solo, visto que nesse ambiente semiárido as respostas que a vegetação apresenta diante da presença ou ausência de chuva são muito rápidas. Nesse sentido, os resultados mostram que uma análise espaço-temporal, utilizando um índice de vegetação, pode estabelecer uma melhor distinção das categorias atribuídas em uma classificação de padrões de cobertura do solo, possibilitando uma melhor percepção do comportamento da vegetação para um período de 24 meses observado.

The Caatinga is a unique biome that only occurs in the semi-arid region of Brazil. This biome is distinguished, mainly, by the capacity to develop mechanisms of adaptation to the low rainfall rates of the region. Plus, it also has a high resilience level upon high anthropic pressure. Considering that land cover plays a very important role in environmental balance, remote sensing techniques have been widely used to extract biophysical information from vegetation. The objective of this work is to establish a methodology that incorporates a time…

Advisors/Committee Members: RUFINO, Iana Alexandra Alves., SANTOS, Carlos Antônio Costa dos., FALCÃO, Ermano Cavalcante..

Subjects/Keywords: Cobertura do Solo; Métodos de Classificação de Imagens; Séries Temporais de Imagens; Soil Coverage; Image Classification Methods; Temporal Image Serials

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SILVA, J. N. d. C. (2017). Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru. (Masters Thesis). Universidade Federal de Campina Grande; PÓS-GRADUAÇÃO EM RECURSOS NATURAIS; UFCG; Brasil; Centro de Tecnologia e Recursos Naturais – CTRN. Retrieved from http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1704

Chicago Manual of Style (16th Edition):

SILVA, João Nailson de Castro. “Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru.” 2017. Masters Thesis, Universidade Federal de Campina Grande; PÓS-GRADUAÇÃO EM RECURSOS NATURAIS; UFCG; Brasil; Centro de Tecnologia e Recursos Naturais – CTRN. Accessed April 16, 2021. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1704.

MLA Handbook (7th Edition):

SILVA, João Nailson de Castro. “Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru.” 2017. Web. 16 Apr 2021.

Vancouver:

SILVA JNdC. Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru. [Internet] [Masters thesis]. Universidade Federal de Campina Grande; PÓS-GRADUAÇÃO EM RECURSOS NATURAIS; UFCG; Brasil; Centro de Tecnologia e Recursos Naturais – CTRN; 2017. [cited 2021 Apr 16]. Available from: http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1704.

Council of Science Editors:

SILVA JNdC. Análise temporal de índices de vegetação no apoio à classificação de imagens: cobertura do solo na bacia hidrográfica do Rio Sucuru. [Masters Thesis]. Universidade Federal de Campina Grande; PÓS-GRADUAÇÃO EM RECURSOS NATURAIS; UFCG; Brasil; Centro de Tecnologia e Recursos Naturais – CTRN; 2017. Available from: http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1704


University of Texas – Austin

3. -6838-2151. Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks.

Degree: MSin Engineering, Mechanical Engineering, 2019, University of Texas – Austin

Working in hazardous environments requires routine inspections in order to meet safety standards. Dangerous quantities of nuclear contamination can exist in infinitesimally small volumes. In order to confidently inspect a nuclear environment for radioactive sources, especially those which emit alpha radiation, technicians must carefully maintain detectors at a consistent velocity and distance from a source. Technicians must also take careful records of which areas have been surveyed or not are important so that no area is left unmonitored. This is a difficult, exhausting task when the coverage area is larger than an office space. An autonomous mobile robotic platform with Complete Coverage Path Planning (CCPP) can reduce dangerous exposure to humans and provide better information for Radiological Control Technicians (RCT). The developed robotic system - or RCTbot - is designed for long-term deployment with little human correction, intervention, or maintenance required. To do this, the RCTbot creates a map of the environment, continually updates it based on multiple sensor inputs, and searches its map for contamination. In nuclear environments, the areas of interest often remain spatially constant throughout the duration of an inspection and are considered temporally static. The RCTbot monitors temporally static environments but adapts to dynamic changes over time. It then uses its sensor data to update and maintain its map so no manual human intervention is necessary. The spatio-temporal map maintenance (STMM) is agnostic to the survey type, so the RCTbot system is viable for application domain other than nuclear. Advisors/Committee Members: Landsberger, Sheldon (advisor), Pryor, Mitchell Wayne (advisor).

Subjects/Keywords: Robotics; Radiation; Mobile robot; Spatio-temporal maps; Radiological Control Technicians; Autonomous mobile robots; RCTbot; Complete Coverage Path Planning; Nuclear contamination; Nuclear environment inspections

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

-6838-2151. (2019). Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72719

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-6838-2151. “Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks.” 2019. Masters Thesis, University of Texas – Austin. Accessed April 16, 2021. http://hdl.handle.net/2152/72719.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-6838-2151. “Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks.” 2019. Web. 16 Apr 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6838-2151. Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks. [Internet] [Masters thesis]. University of Texas – Austin; 2019. [cited 2021 Apr 16]. Available from: http://hdl.handle.net/2152/72719.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6838-2151. Spatio-temporal map maintenance for extending autonomy in long-term mobile robotic tasks. [Masters Thesis]. University of Texas – Austin; 2019. Available from: http://hdl.handle.net/2152/72719

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

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